Griet Neukermans1,2
Kevin Ruddick1
Quinten Vanhellemont1
Naomi Greenwood3
Diurnal variability of turbidity and light attenuation in the southern North Sea from the geostationary SEVIRI sensor
1Management Unit of the North Sea Mathematical Models (MUMM), Belgium 2Université du Littoral Côte d’Opale, Laboratoire d'Océanologie et Géosciences (LOG), France 3Center for Environment, Fisheries and Aquaculture Science (CEFAS), UK
Publication in review in Remote Sensing of the Environment
SEVIRI full disk
Every 15 minutes
0.0
0.2
0.4
0.6
0.8
1.0
0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8
w(l
), a
tmo
spher
ic tra
nsm
itta
nce
l (mm)
H20
OZONE
MOL-SCAT
HRV
VIS0.6
VIS0.8
NIR1.6
R
NIR
HRV
spect
ral re
sponse
wavelength (mm)
Study area
Viewing zenith angle (°)
3 x 3 km²
1 x 1 km²
3 x 6 km²
1 x 2 km²
Neukermans et al. (2009). Mapping SPM from geostationary satellites... Optics Express
)6.0(0w
SEVIRI optimal retrieval )6.0(0w
Digitization Turbid water (assumption of constant s )
)6.0(0,mw
08.0004.0 )6.0(0 w
Optimal range
e = 0.84 e = 1.02 e = 1.32 ?
)(
)8.0(
,0
)8.0()6.0()6.0(0
es
es
av
ccw
t
Neukermans G. (2012). Ph.D. dissertation.
SEVIRI vs. MODIS marine reflectance 8
March
20
09
, 13
h U
TC
6 M
ay 20
08
, 13
h U
TC )6.0(0
wSEVIRI
)6.0(0wSEVIRI
)645(0 MwMODIS
)645(0 MwMODIS
Neukermans G. (2012). Ph.D. dissertation.
in situ T and KPAR data: SmartBuoys
Mills et al. (2003)
in situ T and KPAR every 30 minutes
PAR
0+, 1, 2 m
T TH1
WG
D
T (FNU) on 11 February 2008, 12:00 h UTC
)2(PAR
)1(PARlogKPAR
m
m
Retrieval algorithms for T and KPAR
Turbidity (T) and [SPM]
algorithm (Nechad et al. 2009,
2010):
Attenuation of PAR (KPAR)
algorithm (Devlin et al. 2008):
]SPM[066.0325.0KPAR
2 year dataset (2008-09) of SEVIRI T and KPAR every 15 minutes
)6.0(0
)6.0(0
T
w
w
C
A
SEVIRI vs. in situ T and KPAR atmospheric correction, retrieval algorithms, spatial
resolution, in situ measurement uncertainty
KP
AR
(m
-1)
n r slope offset RMSE 5 50 95
T 3068 0.93 0.82 0.15 5.80 3 29 80
KPAR 1492 0.93 0.85 0.05 0.34 2 18 81
PE (%) percentileslog10 regression
KPAR (m-1)
80% of SEVIRI T is within 53% of in situ T
and
80% of SEVIRI KPAR is within 39% of in situ KPAR
___ 1:1 line
___ fit
___ 1:1 line
___ fit
Diurnal variability of T
Diurnal variability of T
SEVIRI daily composite of 34 images
Quasi cloudfree
MODIS: 1 image
60% clouded
remotely sensed ( ) vs. in-situ ( , ) diurnal variability of turbidity
SB
maxT
t(Tmax)
t( )
SEVIRI ( ) vs. in-situ ( , ) diurnal variability of T
t(Tmax)
t(Tmax) SB
SEVIRI daily composite of 34 images
Quasi cloudfree
MODIS: 1 image
60% clouded
Comparison of T time series
Diurnal variability of T is
picked up well by SEVIRI
with
phase difference generally <1h
1:1 line
+/- 1 h lines
t(T
max
) h U
TC
t(Tmax) h UTC SB
… and KPAR time series
…also picked up well by SEVIRI
t(KPARmax) h UTC SB
t(K
PAR
max
) h U
TC
KP
AR
(m
-1)
KP
AR
(m
-1)
KP
AR
(m
-1)
SEVIRI SmartBuoy
Conclusions • Good correspondence between SEVIRI and
MODIS marine reflectance – Large uncertainties in clear water (digitization) and in
very turbid waters (atmospheric correction)
• On cloudfree days: SEVIRI detects tidal variability of T and Kd in turbid SNS waters – Available for the first time from space
– Applications in ecosystem models, sediment transport modeling, monitoring of T
• Days with moving clouds: significant increase in data availability, compared to polar-orbiters
• Extension of atmospheric correction methodology to full SEVIRI disk or other meteorological sensors…
SEVIRI w
MODIS w
SEVIRI
MODIS
SEVIRI
MSG
MSU
Electro
GOCI
COMS
Where else can this work?
Publications • Neukermans G., 2012. Optical in situ and geostationary satellite-borne
observations of suspended particles in coastal waters. Ph. D. dissertation of the Université du Littoral Côte d’Opale, pp. 210, Academic & Scientific publishers, Brussels, Belgium. ISBN 978 90 7028 949 2
• Neukermans G., K. Ruddick and N. Greenwood. Diurnal variability of turbidity and light attenuation in the southern North Sea from the SEVIRI geostationary sensor. (in review in Remote sensing of the Environment).
• Nechad B., Ruddick, K.G. and G. Neukermans, 2009. Calibration and validation of a generic multisensor algorithm for mapping of turbidity in coastal waters. Proceedings of SPIE "Remote Sensing of the Ocean, Sea Ice, and Large Water Regions" Conference held in Berlin (Germany), 31 August 2009. Proc. SPIE Vol. 7473, 74730H.
• Neukermans G., K. Ruddick, E. Bernard, D. Ramon, B. Nechad and P.Y. Deschamps, 2009. Mapping Total Suspended Matter from geostationary satellites: a feasibility study with SEVIRI in the Southern North Sea. Optics Express, 17(16):14029-14052.